AI Technical Architect - job 2 of 3

As the AI Technical Architect at Capco, your primary responsibilities include developing new functionalities for the GenAI chat platform, optimizing chatbot solutions, and integrating backend systems. You will also be tasked with translating business requirements into workable technology solutions while setting the architectural principles for chatbot development.

To qualify for the AI Technical Architect position at Capco, candidates should have a bachelor's degree in computer science or a related field, alongside demonstrated experience in chatbot solution development, strong programming skills in languages like Python, NodeJS, and Java, and familiarity with cloud technologies, preferably AWS.

The AI Technical Architect plays a crucial role within the Capco Technology Delivery Team, contributing to the design and implementation of innovative AI solutions that align with client needs. This position involves close collaboration with cross-functional Agile teams to deliver effective chatbot functionalities, enhancing client services and fostering innovation.

The AI Technical Architect at Capco works with various technologies, including Large Language Models (LLMs), cloud platforms such as AWS and Azure, and back-end systems integration. Proficiency in developing and consuming APIs, prompt engineering, and understanding the latest trends in AI/ML is essential.

Capco fosters a supportive and collaborative work culture where creativity and innovation thrive. As an AI Technical Architect, you will experience minimal bureaucracy and an entrepreneurial spirit that allows for rapid learning and growth, encouraging you to tackle exciting challenges and contribute meaningfully to client success.

When answering this question, highlight specific projects where you developed chatbot solutions, detailing the technologies used, your approach to problem-solving, and how your solutions effectively met user needs.

Articulate your methodology for gathering business requirements and sharing examples of how you've successfully translated these needs into effective technical solutions, demonstrating your understanding of both the business and technology.

Discuss any projects where you implemented LLMs, explaining your understanding of their capabilities, the advantages they offer, and how you integrated them into solutions, particularly in chatbot frameworks.

Explain the strategies you employ for optimizing performance, including latency reduction, cost-effectiveness, and maintaining high levels of accuracy and security in chatbot interactions.

Share examples of technical challenges you've encountered and how you overcame them, emphasizing your problem-solving skills and your understanding of backend system architectures.

Discuss the resources you utilize to stay informed about industry trends, such as relevant publications, conferences, and online courses, and how you apply new insights into your work.

Focus on a specific instance where you worked closely with stakeholders, detailing how you gathered their input, adapted their needs into a technical plan, and how it led to successful project implementation.

Share your understanding of prompt engineering principles, any relevant projects you've worked on, and how you ensure prompts maximize LLM performance while achieving intended outcomes.

Explain your approach to evaluating overall chatbot effectiveness, including metrics you analyze and how you iterate on feedback to enhance performance.

Discuss the programming languages you are proficient in, providing examples of projects where you used them in AI development, specifically for chatbots and related applications.